ISSN 1000-1239 CN 11-1777/TP

计算机研究与发展 ›› 2016, Vol. 53 ›› Issue (7): 1493-1502.doi: 10.7544/issn1000-1239.2016.20160119

所属专题: 2016绿色计算专题

• 系统结构 • 上一篇    下一篇



  1. (上海交通大学计算机科学与工程系 上海 200240) (
  • 出版日期: 2016-07-01
  • 基金资助: 

Green Hierarchical Management for Distributed Datacenter Containers

Hou Xiaofeng, Song Pengtao, Tang Weichao, Li Chao, Liang Xiaoyao   

  1. (Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240)
  • Online: 2016-07-01

摘要: 近几年,模块化数据中心(集装箱数据中心)因其高能效可拓展的特点而成为极具前景的IT基础设施解决方案.预定制的集装箱数据中心不仅可以被部署在传统仓库级数据中心设施中以支持容量扩展,还能够被部署在城市/郊外以支持物联网数据的本地处理.把传统集中建设和管理的数据中心与地理上分布的模块化数据中心结合起来,能够更加方便地利用本地绿色能源发电以及减少数据传输成本.针对目前涌现的地理上分布的集装箱式数据中心模块提出了一种新型分层化管理模式,该技术将分布式集装箱数据中心逻辑上划分成多个性质和功能不同的层级.一个中央调配系统被用来监控每个层级的集装箱数据中心并施加动态休眠机制以进一步提升数据中心的整体效能.小规模测试实验结果显示分层化管理机制能够提升12%~32%的数据中心整体能效,并且保持较高的服务性能.

关键词: 云计算, 集装箱数据中心, 绿色计算, 分层管理, 性能评估

Abstract: In recent years, modular datacenters (datacenter containers) have become promising IT infrastructure solutions due to their impressive efficiency and scalability. Pre-fabricated containers can be deployed not only in existing warehouse-scale datacenter facilities for capacity expansion, but also in urban/remote areas to support onsite Internet of Things (IoT) data processing. Combing conventional centralized datacenter servers with distributed containers can offer cloud providers new opportunities of exploiting local renewable energy resources and reducing unnecessary data movement overhead. This paper investigates a hierarchical management strategy for emerging geographically distributed datacenter containers. We logically group distributed datacenter containers into multiple classes that have different data accessing patterns. During runtime a central navigation system is used to monitor the utilization of each container class and perform dynamic sleeping scheduling to further improve the overall energy efficiency. Experimental results on our scaled-down test-bed show that the proposed mechanism can save 12%~32% energy cost while ensuring high performance.

Key words: cloud computing, datacenter container, green computing, hierarchical management, performance evaluation